Mahir Musleh
July 30, 2019
-Take a look how some Canadian provinces’ population changed overtime
-Take a look at some regression about what affects the Canadian GNI per capita
We will be using shiny application to create a slider to change the quarter to produce te desired effect on the interactive map. We also will create two additional tabs to inform people about the regression analysis done and plot created on GNI per capita.
Codes for interactive map generation
prov.pop <- fread("./can_pop.csv",stringsAsFactors = FALSE)
colnames(prov.pop)[1] <- "Province"
prov.pop[] <- lapply(prov.pop, function(x) gsub(",","",x))
prov.pop[] <- lapply(prov.pop, function(x) as.character(x))
prov.pop[,2:272] <- lapply(prov.pop[,2:272], function(x) as.numeric(x))
region <- readOGR("./src/ref/ne_50m_admin_1_states_provinces_lakes", encoding='UTF-8')
prov.pop %>% leaflet() %>%
addTiles() %>%
setView(-100, 62, zoom = 3) %>%
addPolygons(data = subset(region, name %in% c("Quebec","British Columbia", "Alberta", "Saskatchewan", "Manitoba", "Ontario", "Quebec", "New Brunswick", "Prince Edward Island", "Nova Scotia", "Newfoundland and Labrador", "Yukon", "Northwest Territories", "Nunavut")),
fillColor = topo.colors(15, alpha = NULL),
weight = 1) %>%
addCircles(popup = paste0(prov.pop$Province),
weight = 4,
radius = (prov.pop$`1952 Q1`)*.015,color = "red")The shiny app will have a slider to change the quarter of the year and the population change, represented by the size of the circle, will change.
Data: World Bank Databank
Values were converted into logarithm form first
Summary
Call:
lm(formula = GNI ~ . - Year, data = indicator.1)
Residuals:
Min 1Q Median 3Q Max
-0.081389 -0.017057 0.001302 0.024043 0.072976
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -10.41019 0.37103 -28.058 < 2e-16 ***
EXP -0.38919 0.09553 -4.074 0.000195 ***
IMP 0.54996 0.12463 4.413 6.75e-05 ***
CONS -0.22028 0.21774 -1.012 0.317356
GEXP 0.65077 0.17751 3.666 0.000673 ***
INV 0.20923 0.05560 3.763 0.000503 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.03616 on 43 degrees of freedom
Multiple R-squared: 0.9976, Adjusted R-squared: 0.9973
F-statistic: 3562 on 5 and 43 DF, p-value: < 2.2e-16Plot